This paper analyses 26 time series that measure daily data for different attributes of the Bitcoin network and studies how the virtual currency behaves compared to a basket of currencies containing the Brazil Real (BRL), the Chinese Yuan (CNY), the Euro (EUR), and the Japan Yen (JPY) against the US Dollar (USD). Basic statistics about the time series have been taken and stationarity has been studied in order to build sterilized fact data and meaningful cointegrations have been found among them. By applying a Vector Autoregressive (VAR) model, a regression has been built among the currencies and the Granger causality test has been applied in order to determine whether one time series (of a given currency) is useful in forecasting another and to observe causal relationships among the currencies studied.

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